The paper investigates the sources of macroeconomic forecast errors in Germany. The predictions of the so-called "six leading" research institutes are analyzed. The forecast errors are discussed within an aggregate demand/supply scheme. Structural Vector Autoregressive Models are estimated to...

Stylized facts suggest that output volatility in OECD countries has declined in recent years. However, the causes and the nature of this decline have so far been analyzed mainly for the United States. In this paper, we analyze whether structural breaks in the dynamics and the volatility of the...

The globalization of international financial markets has renewed interest in the measurement of capital mobility. Consumption-based tests such as the Euler equation test are commonly used. These tests, however, are derived under restrictive assumptions on consumer behavior. In this paper, we ask...

We discuss properties of alternatives or complements to GDP as a measure of welfare at business cycle frequencies. We argue that these figures are not useful to measure the welfare costs of business cycles. First, data is not available at an appropriate quality and frequency. Second, since the...

This paper elaborates on the link between financial market volatility and real economic activity. Using monthly data for Germany from 1968 to 1998, we specify GARCH models to capture the variability of stock market prices, of the real exchange rate, and of a long-term and of a short-term rate of...

This paper elaborates on the link between financial market volatility and real economic activity. Using monthly data for Germany from 1968 to 1998, we specify GARCH models to capture the variability of stock market prices, of the real exchange rate, and of a long-term and of a short-term rate of...

This paper examines the consequences of using "real-time" data for business cycle analysis in Germany based on a novel data set covering quarterly real output data from 1968 to 2001. Real-time output gaps are calculated. They differ considerably from their counterparts based on the most recent...

We use a machine-learning approach known as Boosted Regression Trees (BRT) to reexamine the usefulness of selected leading indicators for predicting recessions. We estimate the BRT approach on German data and study the relative importance of the indicators and their marginal effects on the...

We use a machine-learning approach known as Boosted Regression Trees (BRT) to reexamine the usefulness of selected leading indicators for predicting recessions. We estimate the BRT approach on German data and study the relative importance of the indicators and their marginal effects on the...